Expanded tag genomes for cross-domain recommendation

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Kotkov, Denis and Medlar, Alan and Glowacka, Dorota and Halvey, Martin; Shah, Chirag and White, Ryen W. and Fourney, Adam and Teixeira Lopes, Carla and Trippas, Johanne, eds. (2026) Expanded tag genomes for cross-domain recommendation. In: CHIIR '26: Proceedings of the 2026 Conference on Human Information Interaction and Retrieval. Association for Computing Machinery (ACM), pp. 84-88. ISBN 979-8-4007-2414-5 (https://doi.org/10.1145/3786304.3787950)

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Abstract

Tag genome is widely used in recommender systems research to, for example, measure item similarity, make recommendations and generate recommendation explanations. Applying tag genome to problems in cross-domain recommendation, however, is complicated by the limited item overlap between cross-domain recommendation data sets and the available tag genomes. Furthermore, existing tag prediction models rely on content-based features that are not readily available in a majority of recommendation data sets. To address these issues, we generated tag genomes for both movies and books based on the Amazon data set, which is widely used in cross-domain recommendation research. These new tag genomes are over 200 × larger than the previous versions and can support comparative evaluation of tag-based and collaborative methods, facilitate the development of new cross-domain recommendation algorithms and provide a foundation for studying phenomena, such as serendipity and diversity, across multiple domains. Both data sets and the data generation pipeline are freely available at https://github.com/Bionic1251/Expanded-Tag-Genomes.

ORCID iDs

Kotkov, Denis ORCID logoORCID: https://orcid.org/0000-0003-4729-1995, Medlar, Alan, Glowacka, Dorota and Halvey, Martin ORCID logoORCID: https://orcid.org/0000-0001-6387-8679; Shah, Chirag, White, Ryen W., Fourney, Adam, Teixeira Lopes, Carla and Trippas, Johanne
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